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首页> 外文期刊>American Journal of Chemical Engineering >Development of Model Equations for Predicting Gasoline Blending Properties
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Development of Model Equations for Predicting Gasoline Blending Properties

机译:预测汽油混合特性的模型方程式的开发

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Gasoline blending is of pertinent importance in refinery operations owing to the fact that gasoline gives about 60 - 70 % of the refinery profit. The blending process is essential to obtain gasoline in the demanded quantities and ensure property specifications are met. Two model equations, multivariable nonlinear and multivariable exponential are proposed in this study which are useful in predicting three significant properties of a motor gasoline: research octane number, reid vapour pressure and specific gravity. Gasoline blend data obtained from four different streams: straight run gasoline, straight run naphtha, reformate and fluidized catalytically cracked gasoline have been subjected to multivariate regression analysis with the aid of a statistical software to ascertain the fitness of the proposed equations in predicting the research octane number, reid vapor pressure and the specific gravity of the resulting premium motor spirit. The results of the regression analysis showed that the nonlinear multivariable models proposed gave a good fit as evidenced by the value of the coefficient of determination R2 = 0.988 & 0.994 for the research octane number, 0.853 & 0.883 for the reid vapor pressure and 0.988 for specific gravity. In conclusion, the proposed model equations were fit to the data, found to be adequate, and therefore could be used for prediction of the blend gasoline properties.
机译:由于汽油占炼油厂利润的60%至70%,因此汽油掺混在炼油厂运营中至关重要。混合过程对于获得所需数量的汽油并确保满足性能指标至关重要。本研究提出了两个模型方程,即多元非线性和多元指数,可用于预测汽车汽油的三个重要特性:研究辛烷值,里德蒸气压和比重。借助统计软件,对来自四种不同物流(直馏汽油,直馏石脑油,重整油和流化催化裂化汽油)的汽油混合物数据进行了多元回归分析,以确定拟议方程式在预测研究辛烷值方面的适用性数量,渣油蒸气压力和所产生的优质发动机油的比重。回归分析的结果表明,所提出的非线性多变量模型具有很好的拟合度,正辛烷值的测定系数R2 = 0.988&0.994,里德蒸气压的确定系数R3 = 0.853&0.883,比重为0.988。重力。总之,所提出的模型方程式适合数据,发现是足够的,因此可用于预测混合汽油的性能。

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